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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

The Role of Analysis and Testing in the Service Life Assessment of Ion Engines

Experience from tests and flights and engineering analysis represent the two sources of information on which to base conclusions on the reliability or failure risk of aerospace flight systems. It is rarely feasible to establish high reliability at high confidence by testing aerospace flight systems or components. The limitations of testing in evaluating failure risk are discussed and an alternate statistical approach which relies on both test experience and analysis to quantitatively assess reliability is outlined. The implementation of this methodology in the service life assessment of ion thrusters is discussed and examples of failure modes being addressed in the NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) program are given.

Ion↗
NASA NTRS2013

Unit-Sphere Multiaxial Stochastic-Strength Model Applied to Anisotropic and Composite Materials

Models that predict the failure probability of brittle materials under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This methodology has been extended to predict the multiaxial strength response of transversely isotropic brittle materials, including polymer matrix composites (PMCs), by considering (1) flaw-orientation anisotropy, whereby a preexisting microcrack has a higher likelihood of being oriented in one direction over another direction, and (2) critical strength, or K (sub Ic) orientation anisotropy, whereby the level of critical strength or fracture toughness for mode I crack propagation, K (sub Ic), changes with regard to the orientation of the microstructure. In this report, results from finite element analysis of a fiber-reinforced-matrix unit cell were used with the unit-sphere model to predict the biaxial strength response of a unidirectional PMC previously reported from the World-Wide Failure Exercise. Results for nuclear-grade graphite materials under biaxial loading are also shown for comparison. This effort was successful in predicting the multiaxial strength response for the chosen problems. Findings regarding stress-state interactions and failure modes also are provided.

Nemeth, Noel, N.↗
NASA NTRS2016

Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells

The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.

GMC↗
NASA NTRS1998

Debond Analyses for Stitched Composite Structures

The effect of stitching on mode I and mode II strain energy release rates for debond configurations is studied using an analysis based on plate finite elements and the virtual crack closure technique. The stitches were modeled as discrete nonlinear fastener elements with a compliance determined by experiment. The axial and shear behavior of the stitches was considered with both the compliances and failure loads assumed to be independent. The mode I strain energy release rate, G(sub I), was shown to decrease once the debond had grown beyond the first row of stitches and was reduced to zero for long debonds, however, the mode II strain energy release rate, G(sub II), continued to be of significant magnitude over the range of debond lengths considered.

Glaessgen, E. H.↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a givensystem. As such, it simulates the propagation of failure effects along paths between the origin ofthe system failure modes and points within the system capable of observing the failure effects. Asa result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMsnecessarily contain a significant amount of information about the design, operations, and failuremodes and effects. One of the important benefits of FFMs is that they may be qualitative, ratherthan quantitative and, as a result, may be implemented early in the design process when there ismore potential to positively impact the system design. FFMs may therefore be developed andmatured throughout the monitored system's design process and may subsequently be used toprovide real-time diagnostic assessments that support system operations. This paper provides anoverview of a generalized NASA process that is being used to develop and apply FFMs. FFMtechnology has been evolving for more than 25 years. The FFM development process presented inthis paper was refined during NASA's Ares I, Space Launch System, and Ground SystemsDevelopment and Operations programs (i.e., from about 2007 to the present). Process refinementtook place as new modeling, analysis, and verification tools were created to enhance FFMcapabilities. In this paper, standard elements of a model development process (i.e., knowledgeacquisition, conceptual design, implementation & verification, and application) are describedwithin the context of FFMs. Further, newer tools and analytical capabilities that may benefit thebroader systems engineering process are identified and briefly described. The discussion isintended as a high-level guide for future FFM modelers.

Melcher, Kevin J.↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

Verification↗
NASA NTRS1981

A comprehensive analysis of the performance characteristics of the Mount Laguna solar photovoltaic installation

This paper represents the first comprehensive survey of the Mount Laguna Photovoltaic Installation. The novel techniques used for performing the field tests have been effective in locating and characterizing defective modules. A comparative analysis on the two types of modules used in the array indicates that they have significantly different failure rates, different distributions in degradational space and very different failure modes. A life cycle model is presented to explain a multimodal distribution observed for one module type. A statistical model is constructed and it is shown to be in good agreement with the field data.

Shumka, A.↗
NASA NTRS1994

Designing Bolted Joints Between Composite Plates

Simplified methods developed for use in preliminary design and analysis of bolted joints between flat composite-material plates loaded in tension. Analysis also applicable to joints between composite and metal plates. Methods based on approximate equations for limiting stresses in single-bolt joint in five modes of failure: local-bearing-failure, net tension, wedge-type splitting, shear-out, and tension with shear-out.

Chamis, Christos C.↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
NASA NTRS1986

Robust detection, isolation and accommodation for sensor failures

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous techniques

Emami-Naeini, A.↗
DOE OSTI2025

Ceramography and Thermal Modelling of Irradiated TRISO Particles using BISON

This study presents a comprehensive analysis of irradiated TRISO fuel particles from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program conducted at the Advanced Test Reactor (ATR) as part of my internship. Failure Analysis using high-resolution microscopy was performed to characterize mechanisms in TRISO particle layers, including the kernel, buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) coatings. Failure modes were systematically classified. Thermal conductivity properties of each TRISO layer were evaluated through experimental measurements and computational models for use in BISON finite element code. Experimental thermal conductivity values ranged from 0.5 W/m·K for the buffer layer to 168 W/m·K for SiC, while BISON simulations provided averaged values of 0.57 W/m·K (buffer), 4.0 W/m·K (PyC layers), and 15.95 W/m·K (SiC). Temperature-dependent correlations from PARFUME were implemented for kernel thermal properties.

BISON↗
NASA NTRS2007

Crew Exploration Vehicle Ascent Abort Coverage Analysis

An important element in the design of NASA's Crew Exploration Vehicle (CEV) is the consideration given to crew safety during various ascent phase failure scenarios. To help ensure crew safety during this critical and dynamic flight phase, the CEV requirements specify that an abort capability must be continuously available from lift-off through orbit insertion. To address this requirement, various CEV ascent abort modes are analyzed using 3-DOF (Degree Of Freedom) and 6-DOF simulations. The analysis involves an evaluation of the feasibility and survivability of each abort mode and an assessment of the abort mode coverage using the current baseline vehicle design. Factors such as abort system performance, crew load limits, thermal environments, crew recovery, and vehicle element disposal are investigated to determine if the current vehicle requirements are appropriate and achievable. Sensitivity studies and design trades are also completed so that more informed decisions can be made regarding the vehicle design. An overview of the CEV ascent abort modes is presented along with the driving requirements for abort scenarios. The results of the analysis completed as part of the requirements validation process are then discussed. Finally, the conclusions of the study are presented, and future analysis tasks are recommended.

Abadie, Marc J.↗
NASA NTRS2006

Model-Based Safety Analysis

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Joshi, Anjali↗
NASA NTRS2013

Memory Circuit Fault Simulator

Spacecraft are known to experience significant memory part-related failures and problems, both pre- and postlaunch. These memory parts include both static and dynamic memories (SRAM and DRAM). These failures manifest themselves in a variety of ways, such as pattern-sensitive failures, timingsensitive failures, etc. Because of the mission critical nature memory devices play in spacecraft architecture and operation, understanding their failure modes is vital to successful mission operation. To support this need, a generic simulation tool that can model different data patterns in conjunction with variable write and read conditions was developed. This tool is a mathematical and graphical way to embed pattern, electrical, and physical information to perform what-if analysis as part of a root cause failure analysis effort.

Sheldon, Douglas J.↗
DOE OSTI2024

Leveraging Optimal Sparse Sensor Placement to Aggregate a Network of Digital Twins for Nuclear Subsystems

Nuclear power plants (NPPs) require continuous monitoring of various systems, structures, and components to ensure safe and efficient operations. The critical safety testing of new fuel compositions and the analysis of the effects of power transients on core temperatures can be achieved through modeling and simulations. They capture the dynamics of the physical phenomenon associated with failure modes and facilitate the creation of digital twins (DTs). Accurate reconstruction of fields of interest (e.g., temperature, pressure, velocity) from sensor measurements is crucial to establish a two-way communication between physical experiments and models. Sensor placement is highly constrained in most nuclear subsystems due to challenging operating conditions and inherent spatial limitations. This study develops optimized data-driven sensor placements for full-field reconstruction within reactor and steam generator subsystems of NPPs. Optimized constrained sensors reconstruct field of interest within a tri-structural isotropic (TRISO) fuel irradiation experiment, a lumped parameter model of a nuclear fuel test rod and a steam generator. The optimization procedure leverages reduced-order models of flow physics to provide a highly accurate full-field reconstruction of responses of interest, noise-induced uncertainty quantification and physically feasible sensor locations. Accurate sensor-based reconstructions establish a foundation for the digital twinning of subsystems, culminating in a comprehensive DT aggregate of an NPP.

42 ENGINEERING↗
NASA NTRS1979

Testing of containers made of glass-fiber reinforced plastic with the aid of acoustic emission analysis

Acoustic emission analysis as a quasi-nondestructive test method makes it possible to differentiate clearly, in judging the total behavior of fiber-reinforced plastic composites, between critical failure modes (in the case of unidirectional composites fiber fractures) and non-critical failure modes (delamination processes or matrix fractures). A particular advantage is that, for varying pressure demands on the composites, the emitted acoustic pulses can be analyzed with regard to their amplitude distribution. In addition, definite indications as to how the damages occurred can be obtained from the time curves of the emitted acoustic pulses as well as from the particular frequency spectrum. Distinct analogies can be drawn between the various analytical methods with respect to whether the failure modes can be classified as critical or non-critical.

Wolitz, K.↗